Four Hours and Fifty Minutes: A Workflow Analysis of Patient Flow Through a Composite Emergency Department
Student Name
Master of Science in Nursing Program, Aspen University
N537: Health Care Informatics
Instructor Name
Month Day, Year
Four Hours and Fifty Minutes: A Workflow Analysis of Patient Flow Through a Composite Emergency Department
Workflow analysis examines how work actually moves through a process: who does what, in what order, with what information, and how long each step takes. In informatics, it is the foundation for designing systems that support work rather than disrupt it. This paper analyzes the flow of a typical admitted patient through a composite emergency department, maps each step and its time, identifies the bottlenecks, and recommends changes in which information technology plays a specific role.
Workflow Concepts
Unertl et al. (2010) reviewed workflow research in health care and found that the term is used inconsistently. They proposed a framework that distinguishes the actors who perform work, the artifacts they use, such as records and devices, the actions they take, the characteristics of those actions, including their sequence and timing, and the outcomes. Their review emphasized that workflow includes communication, coordination, and interruptions, not only the formal sequence of tasks. This analysis uses those elements: for each step it identifies the actor, the artifact, the action, and the time.
The Current Workflow
The composite Riverbend Emergency Department sees about 55,000 visits a year and admits 22 percent of patients. The analysis followed a composite 67-year-old woman with abdominal pain and vomiting who was eventually admitted with a small bowel obstruction. Times were taken from electronic health record time stamps and direct observation over one weekday afternoon.
| Step | Actor and artifact | Action | Elapsed time |
|---|---|---|---|
| Arrival to registration | Registration clerk, EHR registration screen | Quick registration, wristband | 0:00-0:08 |
| Registration to triage | Triage nurse, triage flowsheet | Waits in lobby, then triage and ESI level 3 | 0:08-0:34 |
| Triage to room | Charge nurse, tracking board | Waits for a bed to be cleaned | 0:34-1:22 |
| Room to nurse assessment | Primary nurse, EHR | Assessment, IV, labs drawn per protocol | 1:22-1:40 |
| Room to physician evaluation | Emergency physician, EHR | History, examination, orders for CT | 1:22-2:05 |
| Labs resulted | Laboratory, interface to EHR | Complete blood count and chemistry return | 1:40-2:32 |
| CT ordered to CT read | Radiology, imaging system | Transport, scan, radiologist interpretation | 2:05-3:25 |
| Decision to admit | Emergency physician, surgeon consult | Consult by phone, admission order | 3:25-3:55 |
| Admission to inpatient bed | Bed management, admitting unit | Bed assignment, report, transport | 3:55-4:50 |
Where the Minutes Go
Of the 4 hours and 50 minutes, three segments account for more than half the time: waiting for a room after triage (48 minutes), the imaging cycle from order to interpretation (80 minutes), and waiting for an inpatient bed after the admission decision (55 minutes). The front-end delay reflects bed turnover: the room was occupied by a patient waiting to be discharged and then needed cleaning, but environmental services learned of the empty room only when a nurse called. The imaging delay included 25 minutes waiting for transport. The admission delay reflects boarding, a system-wide problem in which inpatient capacity limits ED flow.
Several workflow problems appeared that the time stamps alone did not capture. The triage nurse entered vital signs twice, once on paper during a busy moment and later into the EHR. The primary nurse was interrupted 11 times during the 18-minute assessment. The surgeon's phone consultation was not documented in a structured way, so the admitting team asked the same questions again. The patient waited for beds, scanners, and people, but also for information that existed somewhere in the system and had not reached the next person in line.
What the Evidence Suggests
Crowding in emergency departments is associated with worse patient outcomes and with staff being unable to follow guideline-recommended care, and a systematic review found that most published research now tests or models possible solutions (Morley et al., 2018). Front-end strategies reviewed by Wiler et al. (2010), such as immediate bedding, placing a provider in triage, and split-flow models that separate lower-acuity from higher-acuity patients, can shorten the time from arrival to provider evaluation. Boarding, however, is primarily a hospital capacity problem that ED changes alone cannot fix.
Recommendations With an Informatics Role
Bed turnover: integrate the tracking board with environmental services so that a discharge order automatically alerts housekeeping to the room, and display cleaning status on the board. Target: reduce triage-to-room time from 48 to under 25 minutes.
Front end: pilot a provider-in-triage model during peak hours so that imaging and laboratory orders are placed before a room is available, using protocol-based order sets in the EHR.
Imaging: add transport requests to the CT order so that transport is dispatched automatically, and display expected scan time on the tracking board.
Duplicate documentation: provide mobile devices at triage so that vital signs are entered once, directly into the EHR.
Information transfer: create a structured consult note template for phone consultations, visible to the admitting team.
Boarding: share ED boarding data daily with hospital leadership and support earlier inpatient discharges, a hospital-wide change the informatics team can support with a real-time capacity dashboard.
Measuring the Redesigned Workflow
A workflow analysis is only as useful as the follow-up that shows whether changes worked. Because the EHR already time-stamps most steps, the department can build a monthly report of median times for each segment in the table: arrival to triage, triage to room, room to provider, order to result for laboratory and imaging, decision to admit, and decision to departure. Reporting the segments separately matters, since an improvement at the front end can be hidden by worse boarding times if only total length of stay is tracked. Balancing measures should include patients who leave without being seen and nurse-reported interruptions, so that faster flow does not come at the cost of safety or staff workload. Repeating the direct observation for one afternoon each quarter would capture problems, such as duplicate charting and interruptions, that time stamps cannot show.
Conclusion
Following one patient through the emergency department showed where nearly five hours went: waiting for a clean room, a scan, and an inpatient bed, with information lost and re-entered along the way. Workflow analysis made these delays visible and connected each to a cause. Some can be addressed within the department through integrated tracking, order sets, and structured documentation; others, especially boarding, require hospital-wide action that informatics can inform. Redesigning workflow first and technology second is the lesson of the analysis.
References
Morley, C., Unwin, M., Peterson, G. M., Stankovich, J., & Kinsman, L. (2018). Emergency department crowding: A systematic review of causes, consequences and solutions. PLOS ONE, 13(8), Article e0203316. https://doi.org/10.1371/journal.pone.0203316
Unertl, K. M., Novak, L. L., Johnson, K. B., & Lorenzi, N. M. (2010). Traversing the many paths of workflow research: Developing a conceptual framework of workflow terminology through a systematic literature review. Journal of the American Medical Informatics Association, 17(3), 265-273. https://doi.org/10.1136/jamia.2010.004333
Wiler, J. L., Gentle, C., Halfpenny, J. M., Heins, A., Mehrotra, A., Mikhail, M. G., & Fite, D. (2010). Optimizing emergency department front-end operations. Annals of Emergency Medicine, 55(2), 142-160. https://doi.org/10.1016/j.annemergmed.2009.05.021
How this N 537 Module 4 example is structured
N537 typically includes a workflow analysis of patient flow in the emergency department, tracking time from arrival through registration, triage, nursing, the physician, laboratory and imaging to admission or discharge; the course page places workflow analysis in Module 4. Aspen does not publish module deliverables, so check your classroom for the exact prompt. This example defines workflow with a framework, maps each step with times, locates the bottlenecks and ties each recommendation to an informatics tool.
N537 Module 4 questions, answered
What does N537 Module 4 usually ask for?
The module typically focuses on workflow analysis and documentation design; a common assignment asks for a workflow analysis of patient flow in the emergency department from arrival to admission or discharge. Aspen does not publish module deliverables, so your classroom's instructions govern.
How do I structure a workflow analysis?
Identify each step with its actor, the artifact or system used, the action and the time, then find the longest delays and their causes, including duplicated documentation, interruptions and lost information, and recommend targeted changes.
Can informatics fix ED boarding?
Not alone. Boarding reflects inpatient capacity, so it needs hospital-wide action, but informatics can support it with real-time capacity dashboards and data that show leaders where discharges and bed assignments are delayed.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Aspen University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.